Department of Radiology, New York University, New York, New York, USA.
Magn Reson Med. 2012 Jan;67(1):89-97. doi: 10.1002/mrm.22982. Epub 2011 Jun 23.
Diffusion-weighted imaging (DWI) involves data acquisitions at multiple b values. In this paper, we presented a method of selecting the b values that maximize estimation precision of the biexponential analysis of renal DWI data. We developed an error propagation factor for the biexponential model, and proposed to optimize the b-value samplings by minimizing the error propagation factor. A prospective study of four healthy human subjects (eight kidneys) was done to verify the feasibility of the proposed protocol and to assess the validity of predicted precision for DWI measures, followed by Monte Carlo simulations of DWI signals based on acquired data from renal lesions of 16 subjects. In healthy subjects, the proposed methods improved precision (P = 0.003) and accuracy (P < 0.001) significantly in region-of-interest based biexponential analysis. In Monte Carlo simulation of renal lesions, the b-sampling optimization lowered estimation error by at least 20-30% compared with uniformly distributed b values, and improved the differentiation between malignant and benign lesions significantly. In conclusion, the proposed method has the potential of maximizing the precision and accuracy of the biexponential analysis of renal DWI.
扩散加权成像(DWI)涉及在多个 b 值下采集数据。本文提出了一种选择 b 值的方法,该方法可以最大程度地提高肾脏 DWI 数据双指数分析的估计精度。我们为双指数模型开发了一个误差传播因子,并通过最小化误差传播因子来优化 b 值采样。对四名健康人类受试者(共 8 个肾脏)进行了前瞻性研究,以验证所提出方案的可行性,并评估 DWI 测量预测精度的有效性,然后基于 16 名受试者的肾脏病变采集的数据对 DWI 信号进行了蒙特卡罗模拟。在健康受试者中,与基于感兴趣区的双指数分析中均匀分布的 b 值相比,所提出的方法显著提高了精度(P = 0.003)和准确性(P < 0.001)。在肾脏病变的蒙特卡罗模拟中,与均匀分布的 b 值相比,b 值采样优化将估计误差降低了至少 20-30%,并显著提高了良恶性病变的区分能力。总之,所提出的方法有可能最大限度地提高肾脏 DWI 的双指数分析的精度和准确性。